A generally-used method for restoring a degraded image degraded due to blur, noise, and low resolution includes MAP estimation (Maximum a Posteriori Estimation). The MAP estimation is a method to obtain an optimized result using a-priori knowledge about an amount to be estimated. Therefore, in the MAP estimation, it is important what kind of a-priori knowledge is used. For example, NPLs 1, 2 describe methods for restoring a degraded image by obtaining a-priori knowledge through learning and performing MAP estimation.
NPL 1 describes a method for specializing in restoring a facial image, obtaining a-priori knowledge about a facial image through learning, and performing MAP estimation based on the a-priori knowledge. In addition, the NPL 1 also describes a case for specializing in restoring a character image, obtaining a-priori knowledge about a character image through learning, and performing MAP estimation based on the a-priori knowledge.
NPL 2 describes a method for restoring a general image, and the method includes obtaining a-priori knowledge about a general image through learning and performing MAP estimation based on the a-priori knowledge.